PocketDTA: an advanced multimodal architecture for enhanced prediction of drug−target affinity from 3D structural data of target binding pockets

Authors

Shaoping Shi (ORCID: https://orcid.org/0000-0003-0045-868X)
Long Zhao (ORCID: https://orcid.org/0000-0003-3503-2371)
Hongmei Wang (ORCID: https://orcid.org/0000-0002-4538-906X)

Institutions

Jiangxi University of Water Resources and Electric Power (CN)
Nanchang University (CN)
Nanchang Institute of Science & Technology (CN)
Czech Academy of Sciences, Institute of Mathematics (CZ)

Publication Details

Journal: Bioinformatics
Published: 2024-10-01
DOI: https://doi.org/10.1093/bioinformatics/btae594
Citations: 24
Primary Topic: Computational Drug Discovery Methods
Type: article
Field-Weighted Citation Impact: 8.67

Funders

National Natural Science Foundation of China
Natural Science Foundation of Jiangxi Province

Controls

|||

ALL TIME

JAN

FEB

MAR

APR

MAY

JUN

JUL

AUG

SEP

OCT

article

PocketDTA: an advanced multimodal architecture for enhanced prediction of drug−target affinity from 3D structural data of target binding pockets

Shaoping Shi, Long Zhao, Hongmei Wang

Oct 1, 2024

24 citations

Bioinformatics

Computational Drug Discovery Methods

8.67

article

PocketDTA: an advanced multimodal architecture for enhanced prediction of drug−target affinity from 3D structural data of target binding pockets

Shaoping Shi, Long Zhao, Hongmei Wang

October 1, 2024article en

24 citations

Abstract

No abstract available for this paper.

BioinformaticsVol. 40(10)

Jiangxi University of Water Resources and Electric Power (CN), Nanchang University (CN), Nanchang Institute of Science & Technology (CN), Czech Academy of Sciences, Institute of Mathematics (CZ)

National Natural Science Foundation of China, Natural Science Foundation of Jiangxi Province

Openalex Percentile: Top 2%

Computational Drug Discovery Methods

8.67

DOI Open Access PDF OpenAlex

AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.